Structural equation modeling in cloud computing studies: a systematic literature review

Abstract

Purpose

This study aims to examine the current state of literature on structural equation modeling (SEM) studies in “cloud computing” domain with respect to study domains of research studies, theories and frameworks they use and SEM models they design.

Design/methodology/approach

Systematic literature review (SLR) protocol is followed. In total, 96 cloud computing studies from 2009 to June 2018 that used SEM obtained from four databases are selected, and relevant data are extracted to answer the research questions.

Findings

A trend of increasing SEM usage over years in cloud studies is observed, where technology adoption studies are found to be more common than the use studies. Articles appear under four main domains, namely, business, personal use, education and health care. Technology acceptance model (TAM) is found to be the most commonly used theory. Adoption, intention to use and actual usage are the most common selections for dependent variables in SEM models, whereas security and privacy concerns, costs, ease of use, risks and usefulness are the most common selections for causal factors.

Originality/value

Previous cloud computing SLR studies did not focus on statistical analysis method used in primary studies. This review will display the current state of SEM studies in cloud domain for all future academics and practical professionals.

Citation

Pişirir, E., Uçar, E., Chouseinoglou, O. and Sevgi, C. (2020), "Structural equation modeling in cloud computing studies: a systematic literature review", Kybernetes, Vol. 49 No. 3, pp. 982-1019. https://doi.org/10.1108/K-12-2018-0663